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 Seth-David Donald Dworman \\
1 Wildewood Drive \\
Paxton, MA 01612 \\
(860) 254-7711 \\
sdworman@brandeis.edu
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March 13, 2014
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BBN Technologies \\
10 Moulton Street \\
Cambridge, MA 02138
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Dear BBN Technologies,
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I am a senior majoring in both Linguistics and Computer Science graduating from Brandeis University in May.  I am writing to express my interest in the position of Associate Scientist for which I believe I am a very strong candidate.  During my research internship this past summer, I was introduced to BBN Technologies while working alongside David McDonald, a former employee, who is now a Senior Researcher at Smart Information Flow Technologies.  My skillset and experience in automatic text analysis, semantic/syntactic parsers, machine learning, natural language annotation, and theoretical linguistics would be a great asset to any NLP research.  
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My research internship focused on automatic understanding of natural language and extraction of specific information from news articles.  This is exactly the same kind of work that Elizabeth Boschee, a Lead Scientist in the Speech, Language and Media group mentioned in her video under "Meet the Scientist" on the company website.  Specifically, I had learn to work and interface with \emph{sparser}, an intricate natural language parser written in Lisp that analyzes English text through a semantic grammar with limited syntactic rules.  I learned Lisp on the fly and developed an entirely new sublanguage for the domain of disease in news articles, that answered questions such as which diseases are epidemic, which geographic areas are they confined to, how many cases of the disease are known, what are the vectors of transmission (e.g. human, avian, etc.), how many people have been affected/killed, etc.  One of the more rewarding experiences was collaborating with the architect of \emph{sparser}, David McDonald, who pushed me and encouraged my creativity to develop the \emph{disease} sublanguage.  
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In addition to my internship experience, I have also analyzed large amounts of linguistic data.  In the first semester of Junior year, I successfully completed Statistical Approaches to Natural Language Processing, the second year master's course for the Computational Linguistics program at Brandeis University.  I implemented several machine learning algorithms and studied the mathematics behind them in depth.  These included Naive Bayes classifiers, Hidden Markov Models,  and Maximum Entropy classifiers, which I then applied to linguistic data (IOB chunking, document classification, dependency parsing, etc.).  Machine learning is also central part of my Linguistics senior thesis, whose initial findings I presented this March at the Toronto Undergraduate Linguistics Conference as "Crude Phonotactics: Evidence of UG in Conditional Random Field weights."  Specifically, I have been using HMMs and linear-chain Conditional Random Fields to uncover patterns in phonetically transcribed child speech from the CHILDES database to find evidence of Linguistic theories of Language Acquisition.  A large part of this task involves creating and maintaining a corpus of thousands of utterances over two languages (French, English) in Python.  Finally, in the course on Natural Language Annotation for Machine Learning, I collaborated with a group of four Computational Linguistics master's students to come up with a markup language for capturing sarcasm in Amazon product reviews.  I was in charge of both gathering the dataset and handling the machine learning aspect of the project, i.e. how well did the markup language capture features of sarcastic reviews?  I learned how to gather corpora and tailor these towards a specific task.  
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I would appreciate the opportunity to interview at BBN Technologies and to learn about the current projects in the Speech, Language and Multimedia group.  I believe my skills and experience are a great match with any natural language research.  I thank you for considering my application and look forward to hearing back.  
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Sincerely,
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Seth Dworman
%I would love the opportunity to apply my skills and background to the current projects of the Speech, Language and Multimedia group, in addition to the %exciting learning experience this position offers with regards to applications of research in Computational Linguistics.  
%PARAGRAPH THREE: Request a personal interview and indicate your flexibility as to the time and place. Repeat your phone number in the letter and offer %assistance to help in a speedy response. For example, state that you will be in the city where the company is located on a certain date and would like to set %up an interview. Alternatively, state that you will call on a certain date to set up an interview. End the letter by thanking the employer for taking time to %consider your credentials.

%Make your closing statement positive and specific so that the reader will take action.  Reiterate your interest in the position and in having an opportunity to 
%speak with the employer.  Include your contact information - phone number and email - in this section if it is not already listed at the top of your letter.  %Thank the employer for his/ her consideration of your application materials.
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